# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import logging from tika import parser from io import BytesIO from docx import Document from timeit import default_timer as timer import re from deepdoc.parser.pdf_parser import PlainParser from rag.nlp import rag_tokenizer, naive_merge, tokenize_table, tokenize_chunks, find_codec, concat_img, \ naive_merge_docx, tokenize_chunks_docx from deepdoc.parser import PdfParser, ExcelParser, DocxParser, HtmlParser, JsonParser, MarkdownParser, TxtParser from rag.utils import num_tokens_from_string from PIL import Image from functools import reduce from markdown import markdown from docx.image.exceptions import UnrecognizedImageError, UnexpectedEndOfFileError, InvalidImageStreamError class Docx(DocxParser): def __init__(self): pass def get_picture(self, document, paragraph): img = paragraph._element.xpath('.//pic:pic') if not img: return None img = img[0] embed = img.xpath('.//a:blip/@r:embed')[0] related_part = document.part.related_parts[embed] try: image_blob = related_part.image.blob except UnrecognizedImageError: logging.info("Unrecognized image format. Skipping image.") return None except UnexpectedEndOfFileError: logging.info("EOF was unexpectedly encountered while reading an image stream. Skipping image.") return None except InvalidImageStreamError: logging.info("The recognized image stream appears to be corrupted. Skipping image.") return None try: image = Image.open(BytesIO(image_blob)).convert('RGB') return image except Exception: return None def __clean(self, line): line = re.sub(r"\u3000", " ", line).strip() return line def __call__(self, filename, binary=None, from_page=0, to_page=100000): self.doc = Document( filename) if not binary else Document(BytesIO(binary)) pn = 0 lines = [] last_image = None for p in self.doc.paragraphs: if pn > to_page: break if from_page <= pn < to_page: if p.text.strip(): if p.style and p.style.name == 'Caption': former_image = None if lines and lines[-1][1] and lines[-1][2] != 'Caption': former_image = lines[-1][1].pop() elif last_image: former_image = last_image last_image = None lines.append((self.__clean(p.text), [former_image], p.style.name)) else: current_image = self.get_picture(self.doc, p) image_list = [current_image] if last_image: image_list.insert(0, last_image) last_image = None lines.append((self.__clean(p.text), image_list, p.style.name if p.style else "")) else: if current_image := self.get_picture(self.doc, p): if lines: lines[-1][1].append(current_image) else: last_image = current_image for run in p.runs: if 'lastRenderedPageBreak' in run._element.xml: pn += 1 continue if 'w:br' in run._element.xml and 'type="page"' in run._element.xml: pn += 1 new_line = [(line[0], reduce(concat_img, line[1]) if line[1] else None) for line in lines] tbls = [] for tb in self.doc.tables: html = "" for r in tb.rows: html += "" i = 0 while i < len(r.cells): span = 1 c = r.cells[i] for j in range(i + 1, len(r.cells)): if c.text == r.cells[j].text: span += 1 i = j i += 1 html += f"" if span == 1 else f"" html += "" html += "
{c.text}{c.text}
" tbls.append(((None, html), "")) return new_line, tbls class Pdf(PdfParser): def __call__(self, filename, binary=None, from_page=0, to_page=100000, zoomin=3, callback=None): start = timer() first_start = start callback(msg="OCR started") self.__images__( filename if not binary else binary, zoomin, from_page, to_page, callback ) callback(msg="OCR finished ({:.2f}s)".format(timer() - start)) logging.info("OCR({}~{}): {:.2f}s".format(from_page, to_page, timer() - start)) start = timer() self._layouts_rec(zoomin) callback(0.63, "Layout analysis ({:.2f}s)".format(timer() - start)) start = timer() self._table_transformer_job(zoomin) callback(0.65, "Table analysis ({:.2f}s)".format(timer() - start)) start = timer() self._text_merge() callback(0.67, "Text merged ({:.2f}s)".format(timer() - start)) tbls = self._extract_table_figure(True, zoomin, True, True) # self._naive_vertical_merge() self._concat_downward() # self._filter_forpages() logging.info("layouts cost: {}s".format(timer() - first_start)) return [(b["text"], self._line_tag(b, zoomin)) for b in self.boxes], tbls class Markdown(MarkdownParser): def __call__(self, filename, binary=None): if binary: encoding = find_codec(binary) txt = binary.decode(encoding, errors="ignore") else: with open(filename, "r") as f: txt = f.read() remainder, tables = self.extract_tables_and_remainder(f'{txt}\n') sections = [] tbls = [] for sec in remainder.split("\n"): if num_tokens_from_string(sec) > 3 * self.chunk_token_num: sections.append((sec[:int(len(sec) / 2)], "")) sections.append((sec[int(len(sec) / 2):], "")) else: if sec.strip().find("#") == 0: sections.append((sec, "")) elif sections and sections[-1][0].strip().find("#") == 0: sec_, _ = sections.pop(-1) sections.append((sec_ + "\n" + sec, "")) else: sections.append((sec, "")) for table in tables: tbls.append(((None, markdown(table, extensions=['markdown.extensions.tables'])), "")) return sections, tbls def chunk(filename, binary=None, from_page=0, to_page=100000, lang="Chinese", callback=None, **kwargs): """ Supported file formats are docx, pdf, excel, txt. This method apply the naive ways to chunk files. Successive text will be sliced into pieces using 'delimiter'. Next, these successive pieces are merge into chunks whose token number is no more than 'Max token number'. """ is_english = lang.lower() == "english" # is_english(cks) parser_config = kwargs.get( "parser_config", { "chunk_token_num": 128, "delimiter": "\n!?。;!?", "layout_recognize": True}) doc = { "docnm_kwd": filename, "title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename)) } doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"]) res = [] pdf_parser = None if re.search(r"\.docx$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") sections, tables = Docx()(filename, binary) res = tokenize_table(tables, doc, is_english) # just for table callback(0.8, "Finish parsing.") st = timer() chunks, images = naive_merge_docx( sections, int(parser_config.get( "chunk_token_num", 128)), parser_config.get( "delimiter", "\n!?。;!?")) if kwargs.get("section_only", False): return chunks res.extend(tokenize_chunks_docx(chunks, doc, is_english, images)) logging.info("naive_merge({}): {}".format(filename, timer() - st)) return res elif re.search(r"\.pdf$", filename, re.IGNORECASE): pdf_parser = Pdf() if parser_config.get("layout_recognize", True) else PlainParser() sections, tables = pdf_parser(filename if not binary else binary, from_page=from_page, to_page=to_page, callback=callback) res = tokenize_table(tables, doc, is_english) elif re.search(r"\.xlsx?$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") excel_parser = ExcelParser() if parser_config.get("html4excel"): sections = [(_, "") for _ in excel_parser.html(binary, 12) if _] else: sections = [(_, "") for _ in excel_parser(binary) if _] elif re.search(r"\.(txt|py|js|java|c|cpp|h|php|go|ts|sh|cs|kt|sql)$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") sections = TxtParser()(filename, binary, parser_config.get("chunk_token_num", 128), parser_config.get("delimiter", "\n!?;。;!?")) callback(0.8, "Finish parsing.") elif re.search(r"\.(md|markdown)$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") sections, tables = Markdown(int(parser_config.get("chunk_token_num", 128)))(filename, binary) res = tokenize_table(tables, doc, is_english) callback(0.8, "Finish parsing.") elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") sections = HtmlParser()(filename, binary) sections = [(_, "") for _ in sections if _] callback(0.8, "Finish parsing.") elif re.search(r"\.json$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") chunk_token_num = int(parser_config.get("chunk_token_num", 128)) sections = JsonParser(chunk_token_num)(binary) sections = [(_, "") for _ in sections if _] callback(0.8, "Finish parsing.") elif re.search(r"\.doc$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") binary = BytesIO(binary) doc_parsed = parser.from_buffer(binary) if doc_parsed.get('content', None) is not None: sections = doc_parsed['content'].split('\n') sections = [(_, "") for _ in sections if _] callback(0.8, "Finish parsing.") else: callback(0.8, f"tika.parser got empty content from {filename}.") logging.warning(f"tika.parser got empty content from {filename}.") return [] else: raise NotImplementedError( "file type not supported yet(pdf, xlsx, doc, docx, txt supported)") st = timer() chunks = naive_merge( sections, int(parser_config.get( "chunk_token_num", 128)), parser_config.get( "delimiter", "\n!?。;!?")) if kwargs.get("section_only", False): return chunks res.extend(tokenize_chunks(chunks, doc, is_english, pdf_parser)) logging.info("naive_merge({}): {}".format(filename, timer() - st)) return res if __name__ == "__main__": import sys def dummy(prog=None, msg=""): pass chunk(sys.argv[1], from_page=0, to_page=10, callback=dummy)